Motor imagery-based brain-computer interfaces (MI-BCI) have been proposed as a means for stroke rehabilitation, which combined with virtual reality allows for introducing game-based interactions into rehabilitation. However, the control of the MI-BCI may be difficult to obtain and users may face poor performance which frustrates them and potentially affects their motivation to use the technology. Decreases in motivation could be reduced by increasing the users' sense of agency over the system. The aim of this study was to understand whether embodiment (ownership) of a hand depicted in virtual reality can enhance the sense of agency to reduce frustration in an MI-BCI task. Twenty-two healthy participants participated in a within-subject study where their sense of agency was compared in two different embodiment experiences: 1) avatar hand (with body), or 2) abstract blocks. Both representations closed with a similar motion for spatial congruency and popped a balloon as a result. The hand/blocks were controlled through an online MI-BCI. Each condition consisted of 30 trials of MI-activation of the avatar hand/blocks. After each condition a questionnaire probed the participants' sense of agency, ownership, and frustration. Afterwards, a semi-structured interview was performed where the participants elaborated on their ratings. Both conditions supported similar levels of MI-BCI performance. A significant correlation between ownership and agency was observed (r = 0.47, p = 0.001). As intended, the avatar hand yielded much higher ownership than the blocks. When controlling for performance, ownership increased sense of agency. In conclusion, designers of BCI-based rehabilitation applications can draw on anthropomorphic avatars for the visual mapping of the trained limb to improve ownership. While not While not reducing frustration ownership can improve perceived agency given sufficient BCI performance. In future studies the findings should be validated in stroke patients since they may perceive agency and ownership differently than able-bodied users.

Brain-computer interfaces (BCIs) provide users with a means to control external devices or applications using only voluntarily produced brain activity. Controlling a BCI through motor imagery is a skill that must be acquired, however, little evidence is available on how the user's agency and frustration are affected by different types of feedback during an interaction with a BCI. This was investigated during a virtual reality interaction where 14 naïve participants controlled an avatar with a BCI while receiving either continuous or discrete feedback on their performance. The agency, frustration, ownership and BCI performance were assessed after each of the two conditions (continuous and discrete feedback). There was no statistical difference between the conditions although the participants generally rated agency higher for the continuous feedback which was also uncorrelated to the BCI performance. This suggests that continuous feedback can be useful for increasing agency for users with poor BCI performance by providing them with some knowledge of performance.

This workshop will explore future work in the area of intelligent, conversational, data-driven health interfaces both from patients' and health care professionals' perspectives. We aim to bring together a diverse set of experts and stakeholders to jointly discuss the opportunities and challenges at the intersection of public health care provisioning, patient and caretaker empowerment, monitoring provisioning of health care and its quality. This will require AI-supported, conversational decision-making interfaces that adhere to ethical and privacy standards and address issues around agency, control, engagement, motivation, and accessibility. The goal of the workshop is to create a community around intelligent data-driven interfaces and create a road map for their future research.CCS Concepts: • Human-centered computing → Human computer interaction (HCI).

Adaptive robots have the potential to support the overloaded healthcare system by helping new stroke survivors learn about their conditions. However, current adaptive robots often fail to maintain users' engagement during interactions. This study investigated the impact of an adaptive robot on Social Agency which has been proposed to influence engagement during learning. Twenty-four healthy subjects participated in a study where they learned about stroke symptoms from a robot providing social cues either 1) when their engagement measured by a Brain-Computer Interface (BCI) decreased or 2) at random intervals. While the results confirmed that Social Agency correlated with Engagement, the robot's adaptive behaviour did not increase Social Agency, Engagement, and Information Recall. Using qualitative methods, we propose that adaptive robots need to explicitly acknowledge users to increase Social Agency. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI.

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